Dynamic adjustment of vehicular micro cloud properties

ABSTRACT

Systems, methods, and other embodiments described herein relate to dynamically updating an existing vehicular micro cloud. In one embodiment, a method includes determining one or more parameters of an environment around a plurality of vehicles, and identifying an impact of the one or more parameters of the environment on one or more of the plurality of vehicles associated with the existing vehicular micro cloud. The method includes identifying one or more properties of the existing vehicular micro cloud. The method includes determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact, and updating the one or more properties based on the determination.

TECHNICAL FIELD

The subject matter described herein relates, in general, to systems andmethods for adjusting one or more properties of an existing vehicularmicro cloud.

BACKGROUND

Some connected vehicles can form groups of interconnected vehicles so asto share resources as the interconnected vehicles navigate through anenvironment. Vehicle members of the group, which is known as a“vehicular micro cloud” can be located within a similar geographiclocation.

Properties of a vehicular micro cloud are set when the vehicular microcloud is formed, and can remain static. As such, a change in theenvironment can leave vehicle members unable to share resources tonavigate the change in the environment as the vehicular micro cloud withits static properties becomes obsolete

SUMMARY

In one embodiment, a method for dynamically updating an existingvehicular micro cloud is disclosed. The method includes determining oneor more parameters of an environment around a plurality of vehicles, andidentifying an impact of the one or more parameters of the environmenton one or more of the plurality of vehicles associated with the existingvehicular micro cloud. The method also includes identifying one or moreproperties of the existing vehicular micro cloud. The method includesdetermining which adjustment to the one or more properties of theexisting vehicular micro cloud can address the impact, and updating theone or more properties based on the determination.

In another embodiment, a system for dynamically updating an existingvehicular micro cloud is disclosed. The system includes one or moreprocessors, and a memory in communication with the one or moreprocessors. The memory stores an environment parameter determinationmodule including instructions that when executed by the one or moreprocessors cause the one or more processors to determine one or moreparameters of an environment around a plurality of vehicles. The memorystores an impact detection module including instructions that whenexecuted by the one or more processors cause the one or more processorsto identify an impact of the one or more parameters of the environmenton one or more of the plurality of vehicles associated with the existingvehicular micro cloud. The memory stores a vehicular micro cloud updatemodule including instructions that when executed by the one or moreprocessors cause the one or more processors to identify one or moreproperties of the existing vehicular micro cloud, determine whichadjustment to the one or more properties of the existing vehicular microcloud can address the impact, and update the one or more propertiesbased on the determination.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are incorporated in and constitute apart of the specification, illustrate various systems, methods, andother embodiments of the disclosure. It will be appreciated that theillustrated element boundaries (e.g., boxes, groups of boxes, or othershapes) in the figures represent one embodiment of the boundaries. Insome embodiments, one element may be designed as multiple elements ormultiple elements may be designed as one element. In some embodiments,an element shown as an internal component of another element may beimplemented as an external component and vice versa. Furthermore,elements may not be drawn to scale.

FIG. 1 is an example of a dynamic vehicular micro cloud adjustmentsystem.

FIG. 2 illustrates a block diagram of a vehicle incorporating avehicular micro cloud adjustment system.

FIG. 3 illustrates one embodiment of the vehicular micro cloudadjustment system.

FIG. 4 illustrates a diagram of the vehicular micro cloud adjustmentsystem in a cloud-based configuration.

FIG. 5 is a flowchart illustrating one embodiment of a method associatedwith adjusting properties of an existing vehicular micro cloud.

FIG. 6A is an example of a dynamic vehicular micro cloud adjustmentscenario with an existing vehicular micro cloud.

FIG. 6B is an example of the dynamic vehicular micro cloud adjustmentscenario where the properties of the existing vehicular micro cloud havebeen adjusted.

FIG. 7A is another example of a dynamic vehicular micro cloud adjustmentscenario with an existing vehicular micro cloud.

FIG. 7B is another example of the dynamic vehicular micro cloudadjustment scenario where the properties of the existing vehicular microcloud have been adjusted.

DETAILED DESCRIPTION

Systems, methods, and other embodiments associated with dynamicallyupdating an existing vehicular micro cloud are disclosed. A plurality ofconnected vehicles can form a vehicular micro cloud so that theconnected vehicles (being vehicular micro cloud members) can shareinformation and resources to assist the connected vehicles collaboratingin an environment. Properties of the vehicular micro cloud can beselected based on the characteristics or parameters of the environment.As such, the properties of the vehicular micro cloud are set when thevehicular micro cloud is formed.

The parameters can be influencing parameters for detecting and/ormeasuring an impact on the connected vehicles. The influencingparameters can be intrinsic and related to the vehicular micro cloud.Additionally and/or alternatively, the influencing parameters can beextrinsic and related to the environment. The parameters such as apriority, a task, and/or a purpose of the vehicular micro cloud canchange over time, and with that, the type of resources the connectedvehicles may use to collaborate in the environment can change. As anexample, the connected vehicles can do one or more of assisting eachother, sharing computational resources, communicating with each other,and any other suitable form of collaboration. A vehicular micro cloudset up for connected vehicles in one environment may be unsuitable forthe connected vehicles in another environment.

Accordingly, in one embodiment, the disclosed approach is a system thatdynamically updates an existing vehicular micro cloud. In other words,the system can dynamically update the properties of the existingvehicular micro cloud.

The system can determine the parameters of the environment by receivinginformation about the environment from sensors such as vehicle sensorsor roadside sensors. The information can include information abouttraffic flow or traffic density, vehicle collisions, parked vehicles,road conditions, weather conditions, and/or visibility issues. Theinformation can be static and/or dynamic. Further, the information canbe based on actual and/or predicted values.

The system can determine what the properties of a vehicular micro cloudthat would be suitable in assisting vehicular micro cloud members as thevehicular micro cloud members navigate the environment. The system candetermine whether the properties of the existing vehicular micro cloudare suitable for assisting the vehicular micro cloud members navigatingthrough the environment.

In the case that the system determines that the properties of theexisting vehicular micro cloud are unsuitable, the system can update theproperties of the existing vehicular micro cloud. As an example, thesystem can instruct a vehicular micro cloud member with access to theproperty settings of the vehicular micro cloud to change the properties.

Detailed embodiments are disclosed herein; however, it is to beunderstood that the disclosed embodiments are intended only as examples.Therefore, specific structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a basis for theclaims and as a representative basis for teaching one skilled in the artto variously employ the aspects herein in virtually any appropriatelydetailed structure. Further, the terms and phrases used herein are notintended to be limiting but rather to provide an understandabledescription of possible implementations. Various embodiments are shownin the figures, but the embodiments are not limited to the illustratedstructure or application.

It will be appreciated that for simplicity and clarity of illustration,where appropriate, reference numerals have been repeated among thedifferent figures to indicate corresponding or analogous elements. Inaddition, numerous specific details are set forth in order to provide athorough understanding of the embodiments described herein. However, itwill be understood by those of ordinary skill in the art that theembodiments described herein can be practiced without these specificdetails.

Referring to FIG. 1 , an example of a Dynamic Vehicular Micro CloudAdjustment (DVMCA) system 100 is shown. The DVMCA system 100 may includevarious elements, which may be communicatively linked in any suitableform. As an example, the elements may be connected, as shown in FIG. 1 .Some of the possible elements of the DVMCA system 100 are shown in FIG.1 and will now be described. It will be understood that it is notnecessary for the DVMCA system 100 to have all of the elements shown inFIG. 1 or described herein. The DVMCA system 100 can include one or morecommunication networks 110, one or more vehicular micro clouds 120,and/or one or more servers 130. The DVMCA system 100 may have anycombination of the various elements shown in FIG. 1 . Further, the DVMCAsystem 100 may have additional elements to those shown in FIG. 1 . Insome arrangements, the DVMCA system 100 may not include one or more ofthe elements shown in FIG. 1 . Further, it will be understood that oneor more of these elements may be physically separated by largedistances.

The elements of the DVMCA system 100 may be communicatively linkedthrough the one or more communication networks. As used herein, the term“communicatively linked” can include direct or indirect connectionsthrough a communication channel or pathway or another component orsystem. A “communication network” means one or more components designedto transmit and/or receive information from one source to another. Theone or more of the elements of the DVMCA system 100 may include and/orexecute suitable communication software, which enables the variouselements to communicate with each other through the communicationnetwork and perform the functions disclosed herein.

The one or more communication networks 110 can be implemented as, orinclude, without limitation, a wide area network (WAN), a local areanetwork (LAN), the Public Switched Telephone Network (PSTN), a wirelessnetwork, a mobile network, a Virtual Private Network (VPN), theInternet, one or more intranets, vehicle-to-vehicle (V2V) communication,vehicle-to-cloud (V2C) communication, and/or some other form ofvehicle-to-everything (V2X) wireless communication. The communicationnetwork 110 further can be implemented as or include one or morewireless networks, whether short-range (e.g., a local wireless networkbuilt using a Bluetooth or one of the IEEE 802 wireless communicationprotocols, e.g., 802.11a/b/g/i, 802.15, 802.16, 802.20, Wi-Fi ProtectedAccess (WPA), or WPA2 or long-range (e.g., a mobile, cellular, and/orsatellite-based wireless network; GSM, TDMA, CDMA, WCDMA networks or thelike). The communication network 110 can include wired communicationlinks and/or wireless communication links. The communication network 110can include any combination of the above networks and/or other types ofnetworks.

The DVMCA system 100 can include one or more connected vehicles 102. Asused herein, “vehicle” means any form of motorized transport. In one ormore implementations, the vehicle can be an automobile. Whilearrangements will be described herein with respect to automobiles, itwill be understood that embodiments are not limited to automobiles. Insome implementations, the vehicle may be any device that, for example,transports passengers. In some implementations, the vehicle can be anyother type of vehicle that may be used on a roadway, such as amotorcycle. In some implementation, the vehicle can be a watercraft, anaircraft, or any other form of motorized transport. The connectedvehicle 102 can be a vehicle that is communicatively linked to one ormore elements of the DVMCA system 100.

The DVMCA system 100 can include the one or more vehicular microcloud(s) 120. A vehicular micro cloud 120 is a wireless network systemin which a plurality of the connected vehicles 102, and optionally,devices such as non-vehicle node, form a group of interconnected membervehicles 102. The interconnected member vehicles 102, also known asvehicular micro cloud members, can communicate and share resources witheach other using, as an example, V2V communication. The vehicular microcloud members 102 can include one or more cloud leaders 104. The cloudleader(s) 104 can be the vehicular micro cloud member 102 that forms,maintains and/or updates the vehicular micro cloud 120. The cloud leader104 can determine and/or manage how the computing resources of thevehicular micro cloud 120 are utilized by the vehicular micro cloudmembers 102.

The vehicular micro cloud 120 can have one or more properties disclosedherein. As an example, the properties of the vehicular micro cloud 120can be stored, maintained, and updated by the cloud leader 104. The oneor more properties of the vehicular micro cloud 120 can include apriority. The priority can be a goal for the vehicular micro cloud 120.As an example, the priority of the vehicular micro cloud 120 can besafety, comfort, and time management. In some arrangements, one ofsafety, comfort, and time management can be of higher importance thanthe other two. In a case where the priority of the vehicular micro cloud120 is safety, the vehicular micro cloud 120 can be formed andmaintained to advance the safety of passenger(s) and/or pedestrian(s).As an example, the vehicular micro cloud members 102 can exchangeinformation such as weather conditions, road conditions, and trafficconditions, and share resources to determine safe routes. As anotherexample, if the vehicular micro cloud member 102 has information thatindicates that a driver can be easily distracted, the vehicular microcloud member 102 can share resources to identify and travel on routeswith less or no distractions. In a case where the priority of thevehicular micro cloud 120 is comfort, the vehicular micro cloud 120 canbe formed and maintained to advance the comfort of the passengers. As anexample, the vehicular micro cloud members 102 can share resources toidentify the routes that provide the smoothest rides. The vehicularmicro cloud members 102 can share resources so as to, as an example,drive at a comforting speed and change lanes in a smooth manner. In acase where the priority of the vehicular micro cloud 120 is timemanagement, the vehicular micro cloud 120 can be formed and maintainedto manage the travel time of the passenger(s). The vehicular micro cloudmembers 102 can share resources to determine traffic conditions and thefastest route(s) so as to minimize travel time. In some otherarrangements, two of safety, comfort, and time management can be ofhigher importance than the remaining third. In some other arrangements,safety, comfort, and time management can be of equal importance.

The one or more properties of the vehicular micro cloud 120 can includea mobility type. The mobility type can refer to whether the vehicularmicro cloud 120 is movable or immovable. In such a case, the vehicularmicro cloud 120 can be a stationary vehicular micro cloud 120 or amobile vehicular micro cloud 120. A stationary vehicular micro cloud 120can be tied to a fixed geographic location, e.g., an intersection. Insuch a case, a connected vehicle can join the stationary vehicular microcloud 120 when the connected vehicle is within the fixed geographiclocation of the stationary vehicular micro cloud 120. The connectedvehicle can leave the stationary vehicular micro cloud 120 when theconnected vehicle exits the fixed geographic location of the stationaryvehicular micro cloud 120. A mobile vehicular micro cloud 120 can betied to vehicular micro cloud members that are travelling in the samedirection. The mobile vehicular micro cloud 120 can travel with thevehicular micro cloud members, and as such, the geographic location ofthe mobile vehicular micro cloud 120 moves with the vehicular microcloud members. A connected vehicle can join the mobile vehicular microcloud 120 when the connected vehicle is in an area covered by the mobilevehicular micro cloud 120. The connected vehicle can leave the mobilevehicular micro cloud 120 when the connected vehicle exits the areacovered by the mobile vehicular micro cloud 120.

The one or more properties of the vehicular micro cloud 120 can includean origin type. The origin type can refer to the circumstances underwhich the vehicular micro cloud 120 is formed. As an example, avehicular micro cloud 120 can be a pre-assigned vehicular micro cloud120 or an on-demand vehicular micro cloud 120. A pre-assigned vehicularmicro cloud 120 can be formed independent of an event or an occurrence.The pre-assigned vehicular micro cloud 120 can be formed prior to and inanticipation of an event or occurrence, however the pre-assignedvehicular micro cloud 120 may not formed in response to the event oroccurrence. An on-demand vehicular micro cloud 120 can be formed inresponse to an event or occurrence. As an example, in response to anaccident ahead, connected vehicles can form an on-demand vehicular microcloud 120 such that the vehicular micro cloud members can shareinformation about alternate routes of travel. The on-demand vehicularmicro cloud 120 can exist in response to an event or occurrence and canbe dissolved when the impact of the event or occurrence no longer exist.

The one or more properties of the vehicular micro cloud 120 can includea dependency type. The dependency type can refer to the dependency orlack of dependency of the vehicular micro cloud 120 on other vehicularmicro cloud(s) 120. In such a case, a vehicular micro cloud 120 can bean independent vehicular micro cloud 120 or an interdependent vehicularmicro cloud 120. An independent vehicular micro cloud 120 can includevehicular micro cloud members of the independent vehicular micro cloud120 that can communicate and share resources with each other within theindependent vehicular micro cloud 120. An interdependent vehicular microcloud 120 can include vehicular micro cloud members of theinterdependent vehicular micro cloud 120 that communicate and shareresources with each other within the interdependent vehicular microcloud 120 as well as with member vehicles belonging to anotherinterdependent vehicular micro cloud 120. The vehicular micro cloudmembers in the independent vehicular micro cloud 120 can communicatewith each other in any suitable communication method. The vehicularmicro cloud members in the interdependent vehicular micro clouds 120 cancommunicate with each other in any suitable communication method.

The one or more properties of the vehicular micro cloud 120 can includea scale type. The scale type can refer to the scale of the vehicularmicro cloud 120. In such a case, the vehicular micro cloud 120 canremain small scale as the vehicular micro cloud 120 and can limitcommunication with other vehicular micro clouds 120. The scale type canbe large scale such as a vehicular macro cloud. The vehicular macrocloud can include a plurality of connected vehicles spanning a largegeographical region such as a city. The member vehicles of the vehicularmacro cloud can communicate across a city, as an example, using anysuitable network such as V2V or V2I communication networks. The membervehicles of the vehicular macro cloud can belong to one or morevehicular micro clouds 120. The one or more vehicular micro clouds 120can communicate with each other to form the vehicular macro cloud. Thevehicular micro cloud 120 can include a plurality of connected vehicleswithin a limited geographical region. The member vehicles of thevehicular micro cloud 120 can communicate and share resources with eachother using, as an example, V2V communication. The vehicular micro cloudmembers 102 can include one or more cloud leader vehicles 104 of thevehicular micro cloud 120. The cloud leader vehicle 104 can be themember vehicle that forms, maintains and/or updates the vehicular microcloud 120. The cloud leader vehicle 104 can determine and/or manage howthe computing resources of the vehicular micro cloud 120 are utilized bythe members of the vehicular micro cloud 120.

The one or more properties of the vehicular micro cloud 120 can includea communication category. The communication category can refer to acommunication configuration. As an example, a vehicular micro cloud 120can utilize ad-hoc communication and/or hybrid communication. Membervehicles of a vehicular micro cloud 120 that has the ad-hoccommunication model can communicate with each other using V2Vcommunication. Member vehicles of a vehicular micro cloud 120 that hasthe hybrid communication model can communicate with each other using acombination of V2V communication and V2C communication. Member vehiclesof the vehicular micro cloud 120 can use any suitable means ofcommunication in addition to those mentioned above.

The one or more properties of the vehicular micro cloud 120 can includea collaboration criteria. The collaboration criteria can refer to areason for connected vehicles to collaborate, exchange information,assist each other, and share resources. The collaboration criteria caninclude an objective function. The objective function can be anobjective of the vehicular micro cloud 120. As an example, the objectivefunction can be to improve awareness, which can refer to informingvehicular micro cloud members about an event or occurrence in theenvironment and making the vehicular micro cloud members aware. Asanother example, the objective function can be to mitigate trafficcongestion. As another example, the objective function can be tomitigate stop-and-go traffic. The collaboration criteria can include anoptimization method. The optimization method can be to maximize a goalof the vehicular micro cloud 120 or minimize an impact of theenvironment on the member vehicles. As an example, the optimizationmethod can be to maximize intersection safety. As another example, theoptimization method can be to minimize safety risk. As another example,the optimization method can be to minimize driver situation analysis byproviding speed advisories and lane change recommendations.

The DVMCA system 100 can include the one or more servers 130. Theserver(s) 130 may be, for example, cloud-based server(s) or edge-basedserver(s). The server(s) 130 can communicate with one or more connectedvehicles 102 over a communication module, such as by any type of V2Ccommunications, now known or later developed. The server(s) 130 canreceive data from and send data to the connected vehicle(s) 102.Alternatively and/or additionally, the connected vehicle(s) 102 and theserver(s) 130 may communicate over other suitable means such as V2Xcommunications.

Referring to FIG. 2 , a block diagram of the connected vehicleincorporating a vehicular micro cloud adjustment system 270 isillustrated. The connected vehicle includes various elements. It will beunderstood that in various embodiments, it may not be necessary for theconnected vehicle 102 to have all of the elements shown in FIG. 2 . Theconnected vehicle 102 can have any combination of the various elementsshown in FIG. 2 . Further, the connected vehicle 102 can have additionalelements to those shown in FIG. 2 . In some arrangements, the connectedvehicle 102 may be implemented without one or more of the elements shownin FIG. 2 . While the various elements are shown as being located withinthe connected vehicle 102 in FIG. 2 , it will be understood that one ormore of these elements can be located external to the connected vehicle102. Further, the elements shown may be physically separated by largedistances. For example, as discussed, one or more components of thedisclosed system can be implemented within a vehicle while furthercomponents of the system are implemented within a cloud-computingenvironment, as discussed further subsequently.

Some of the possible elements of the connected vehicle 102 are shown inFIG. 2 and will be described along with subsequent figures. However, adescription of many of the elements in FIG. 2 will be provided after thediscussion of FIGS. 3-7 for purposes of brevity of this description.Additionally, it will be appreciated that for simplicity and clarity ofillustration, where appropriate, reference numerals have been repeatedamong the different figures to indicate corresponding or analogouselements. In addition, the discussion outlines numerous specific detailsto provide a thorough understanding of the embodiments described herein.Those of skill in the art, however, will understand that the embodimentsdescribed herein may be practiced using various combinations of theseelements. In any case, as illustrated in the embodiment of FIG. 2 , theconnected vehicle 102 includes the vehicular micro cloud adjustmentsystem 270 that is implemented to perform methods and other functions asdisclosed herein relating to dynamically updating an existing vehicularmicro cloud 120. As will be discussed in greater detail subsequently,the vehicular micro cloud adjustment system 270, in various embodiments,may be implemented partially within the connected vehicle 102 and mayfurther exchange communications with additional aspects of the vehicularmicro cloud adjustment system(s) 270 that are remote from the connectedvehicle 102 in support of the disclosed functions. Thus, while FIG. 3generally illustrates the vehicular micro cloud adjustment system 270 asbeing self-contained, in various embodiments, the vehicular micro cloudadjustment system 270 may be implemented within multiple separatedevices some of which may be remote from the connected vehicle 102.

With reference to FIG. 3 , one embodiment of the vehicular micro cloudadjustment system 270 of FIG. 2 is further illustrated. The vehicularmicro cloud adjustment system 270 is shown as including a processor 210from the connected vehicle 102 of FIG. 2 . Accordingly, the processor210 can be a part of the vehicular micro cloud adjustment system 270,the vehicular micro cloud adjustment system 270 can include a separateprocessor from the processor 210 of the connected vehicle 102, and/orthe vehicular micro cloud adjustment system 270 may access the processor210 through a data bus or another communication path. In furtheraspects, the processor 210 is a cloud-based resource that communicateswith the vehicular micro cloud adjustment system 270 through acommunication network.

In one embodiment, the vehicular micro cloud adjustment system 270 caninclude a memory 310 that stores an environment parameter determinationmodule 320, an impact identification module 330, and a vehicular microcloud update module 340. The memory 310 is a random-access memory (RAM),read-only memory (ROM), a hard-disk drive, a flash memory, or othersuitable memory for storing the modules 320, 330, and 340. Theenvironment parameter determination module 320, the impactidentification module 330, and the vehicular micro cloud update module340 are, for example, computer-readable instructions within the physicalmemory 310 that when executed by the processor 210 cause the processor210 to perform the various functions disclosed herein.

In one embodiment, the vehicular micro cloud adjustment system 270 caninclude a data store 350. The data store 350 is, in one embodiment, anelectronic data structure (e.g., a database) stored in the memory 310 oranother data store and that is configured with routines that can beexecuted by the processor 210 for analyzing stored data, providingstored data, organizing stored data, and so on. Thus, in one embodiment,the data store 350 can store data used by the modules 320, 330 and 340in executing various functions. In one embodiment, the data store 350can include traffic records data 360, vehicular micro cloud propertiesdata 370, impact and matching properties data 380 and or otherinformation that is used by the modules 320, 330, and 340.

The traffic records data 360 can contain statistical records of pasttraffic information such as traffic patterns based on geographiclocation and time of day. The traffic records data 360 can includepreviously recorded traffic information for the geographic location. Thevehicular micro cloud properties data 370 can include information aboutthe properties of the existing vehicular micro cloud 120. The propertiesare described in detail above. The impact and matching properties data380 can include a database populated with the various types of impactsmatched with the adjustments to the properties of the existing vehicularmicro cloud 120 that can address each of the various impacts. In otherwords, the database can include mapping an impact to vehicular microcloud properties that can address the impact. As an example, an entry inthe database can include the impact being a portion of a road along theroute of travel is inaccessible due to flooding, and the adjustments toaddress the impact can include adjusting priority to safety, mobilitytype to stationary, dependency type to interdependent, communicationcategory to V2C communication, and/or optimization method to maximizesafety while traversing the flooded road. The mapping can be determinedusing any suitable method such as based on a statistical analysis and/ormachine learning algorithms.

In one embodiment, the environment parameter determination module 320can include instructions that function to control the processor 210 todetermine one or more parameters of an environment around a plurality ofvehicles. As such, the environment can be around one or more vehicles.As an example, the vehicle(s) can be member vehicle(s) of the vehicularmicro cloud 120. Alternatively, the vehicle(s) may not be membervehicle(s) of the vehicular micro cloud 120. In such a case and as anexample, the vehicle(s) can be located ahead of the vehicular microcloud 120 along a travel route. As another example, the vehicle(s) canbe located behind the vehicular micro cloud 120 along the route.

The parameter(s) of the environment can be a characteristic of theenvironment that can affect a vehicle travelling in or towards theenvironment. As an example, a parameter can be a vehicle accident thathas occurred in the environment. As another example, a parameter can bea parked or stalled vehicle in the environment. As another example, aparameter can be traffic congestion in the environment. Similar to thevehicle accident and stalled vehicle, the traffic congestion can causethe vehicle to change its travel route and/or recalculate its traveltime. As another example, a parameter can be a road condition in theenvironment. The road condition can be, as an example, road damage suchas a pothole, or road flooding. As another example, a parameter can be aweather condition in the environment. The aforementioned examples ofparameters can cause the vehicle to change its travel route and/orrecalculate its travel time.

The environment parameter determination module 320 can further includeinstructions that function to control the processor to monitor theenvironment. The environment parameter determination module 320 canreceive information about the environment from vehicle sensors.Alternatively and/or additionally, the environment parameterdetermination module 320 can receive information about the environmentfrom external sources. The external sources may include any entitiescapable of wireless communication such as other vehicles, roadsideunits, servers, and/or databases.

The information about the environment can include a weather condition, aroad condition, location of the road segment(s), and/or timestamp. Theweather condition may include, as an example, presence of precipitationsuch as snow, rain, and/or hail. The weather condition may furtherinclude impacts of weather such as fog levels, fallen snow levels (i.e.the amount of snow on the ground), and/or flooding. The weathercondition may be updated periodically and/or on-demand. The roadcondition may include information about the physical condition of theroad segment(s). The road condition may include the presence ofpotholes, road debris, overgrown vegetation, the slope of the roadsegment(s), the curvature of the road segment(s), and/or the frictionlevel of the road segment(s).

The environment parameter determination module 320 can determine theparameters of the environment based on predicting events that can occurin the environment. As an example, the environment parameterdetermination module 320 can access a database such as the data store(s)350 to determine the amount of traffic that can be expected on a certainroad at a certain time and day. As an example, the environment parameterdetermination module 320 can access and process information in thetraffic records data 360 to predict parameters of the environment.

The impact identification module 330 can include instructions thatfunction to control the processor 210 to identify an impact of the oneor more parameters of the environment on one or more of the plurality ofvehicles associated with the existing vehicular micro cloud 120. Thevehicles associated with the existing vehicular micro cloud 120 can bemember vehicles of the existing vehicular micro cloud 120.Alternatively, the vehicles associated with the existing vehicular microcloud 120 can be vehicles that are not member vehicles of the existingvehicular micro cloud 120 but are proximate to the geographical locationof the existing vehicular micro cloud 120.

The impact identification module 330 can use any suitable algorithm suchas a machine learning algorithm or an artificial intelligence process toidentify the impact of the one or more parameters of the environment onthe vehicles associated with the existing vehicular micro cloud 120. Asan example, the impact identification module 330 can determine that theimpact of a vehicle accident on a vehicle can be road closure such thatthe impacted vehicle is unable to traverse along an intended route. Asanother example, the impact identification module 330 can determine thatthe impact of a vehicle accident can be traffic congestion such that theimpacted vehicle encounters a time delay. As another example, the impactidentification module 330 can determine that the impact of a vehicleaccident can result in a safety risk as drivers get distracted as theydrive by and observe the vehicle accident.

The impact identification module 330 can determine the impact of theparameters of the environment on a vehicle based on the parameters ofthe environment and other factors such as time of day and vehiclelocation. As an example, the impact identification module 330 candetermine that the impact on a vehicle is a time delay when there is avehicle accident, and the vehicle is on a high traffic road such as ahighway at a peak time such as an evening rush hour. As another example,the impact identification module 330 can determine that the impact onthe vehicle can be that the intended route of travel is blocked orunavailable when there is flooding or a fallen tree on a road along theintended route.

The vehicular micro cloud update module 340 can include instructionsthat function to control the processor 210 to identify one or moreproperties of the existing vehicular micro cloud 120, determine whichadjustment to the one or more properties of the existing vehicular microcloud 120 can address the impact, and update the one or more propertiesbased on the determination.

The vehicular micro cloud update module 340 can identify the propertiesof the existing vehicular micro cloud 120 by, as an example, requestingthe properties of the existing vehicular micro cloud 120 from the cloudleader. In such a case, the vehicular micro cloud update module 340 canrequest the information from the cloud leader using a suitable means ofcommunication. As another example, the vehicular micro cloud updatemodule 340 can access the properties of the existing vehicular microcloud 120 from the data store(s) 350. In such an example and aspreviously explained, the data store(s) 350 can include vehicular microcloud properties data 370 that contain the properties of the existingvehicular micro cloud 120. The vehicular micro cloud update module 340can receive the information which can include the mobility type, thepriority, the origin type, the size type, communication category, thedependency type, and/or the collaboration criteria of the vehicularmicro cloud 120. As another example, the vehicular micro cloud updatemodule 340 can identify the properties of the existing vehicular microcloud 120 by monitoring or observing the existing vehicular micro cloud120.

The vehicular micro cloud update module 340 can determine whichadjustment to the one or more properties of the existing vehicular microcloud 120 can address the impact to the vehicles. The vehicular microcloud update module 340 can use any suitable algorithm to determinewhich adjustments to the properties of the existing vehicular microcloud 120 can address the impact. As an example, the vehicular microcloud update module 340 can access a database populated with the varioustypes of impacts matched with the adjustments to the properties of theexisting vehicular micro cloud 120 that can address each of the variousimpacts such as the impact and matching properties data 380 in the datastore(s).

The vehicular micro cloud update module 340 can include instructionsthat function to control the processor 210 to update the one or moreproperties based on the determination. The vehicular micro cloud updatemodule 340 can identify an original reason for the existing vehicularmicro cloud 120. The original reason refers to a reason that led to theexisting vehicular micro cloud 120 being formed and/or continuing toexist. The original reason can be based on one or more of traffic flow,traffic density, a vehicle accident, a road closure, an unusual event,and a risk. In other words, the existing vehicular micro cloud 120 canbe formed or can continue to exist to assist vehicles as the vehiclestravel amidst one or more of the traffic flow, the traffic density, thevehicle accident, the road closure, an unusual event, and any otherrisk. The vehicular micro cloud update module 340 can identify theoriginal reason for the existing vehicular micro cloud 120 by requestinginformation about the original reason from a cloud member 102 or a cloudleader 104.

The vehicular micro cloud update module 340 can identify a new reasonfor the existing vehicular micro cloud 120 based on the one or moreparameters of the environment. In other words, the vehicular micro cloudupdate module 340 can identify the new reason for the existing vehicularmicro cloud 120 as a reason that a vehicular micro cloud 120 can beformed or can exist such that the vehicular micro cloud 120 can assistvehicles as the vehicles address the impact of the parameters of theenvironment. The vehicular micro cloud update module 340 can determinethe new reason using any suitable algorithm. As an example, thevehicular micro cloud update module 340 can access a database populatedwith the various parameters matched with the reason for a vehicularmicro cloud 120. The vehicular micro cloud update module 340 candetermine the new reason for the vehicular micro cloud 120 byidentifying the parameters of the environment in the database andretrieving a reason matched to identified parameters.

The vehicular micro cloud update module 340 can determine that theoriginal reason and the new reason are different. In other words, thevehicular micro cloud update module 340 can compare the original reasonand the new reason to determine whether the original reason and the newreason are the same or different.

The vehicular micro cloud update module 340 can, in response todetermining that the original reason and the new reason are different,determine which adjustment to the one or more properties of the existingvehicular micro cloud 120 can address the impact based on the newreason. The vehicular micro cloud update module 340 can update theproperties of the existing vehicular micro cloud 120 based on thedetermined adjustment(s) in response to the original reason and the newreason for the existing vehicular micro cloud 120 being different.

The vehicular micro cloud update module 340 can update the properties bytransmitting the determined properties to the cloud leader 104 using anysuitable communication means. As an example, the vehicular micro cloudupdate module 340 can transmit a message to the cloud leader 104indicating that the properties of the vehicular micro cloud 120 beupdated from stationary to mobile, from independent to interdependent,from time management priority to safety priority, and/or from ad-hoccommunication to hybrid communication. As another example, the vehicularmicro cloud update module 340 can determine that another vehicle 102other than the current cloud leader 104 become the cloud leader 104. Insuch an example, the vehicular micro cloud update module 340 cantransmit a message to the other vehicle 102 requesting the other vehicle102 become the cloud leader 104 and indicating the updated properties ofthe vehicular micro cloud 120.

The vehicular micro cloud adjustment system 270 may be furtherimplemented as a cloud-based system that functions within acloud-computing environment 400 as illustrated in relation to FIG. 4 .That is, for example, the vehicular micro cloud adjustment system 270may acquire telematics data (i.e., sensor data 219) from vehicles andexecute as a cloud-based resource that is comprised of devices (e.g.,distributed servers) remote from the connected vehicle 102 todynamically update the existing vehicular micro cloud 120. Accordingly,the vehicular micro cloud adjustment system 270 may communicate withconnected vehicles (e.g., connected vehicles 410, 420, and 430) that aregeographically distributed. In one approach, the cloud-based vehicularmicro cloud adjustment system 270 can exchange data 350 with componentsor separate instances of the vehicular micro cloud adjustment system 270that are integrated with the connected vehicles 410-430.

Along with the communications, the connected vehicles 410-430 mayprovide sensor data 219. As such, the cloud-based aspects of thevehicular micro cloud adjustment system 270 may then process the sensordata 219 separately for the vehicles 410-430 to determine the one ormore parameters of the environment. In further aspects, thevehicle-based systems may perform part of the processing while thecloud-computing environment 400 may handle a remaining portion orfunction to validate results of the vehicle-based systems. It should beappreciated that apportionment of the processing between the vehicle andthe cloud may vary according to different implementations. Additionalaspects of the cloud computing environment 400 are discussed above inrelation to components of the vehicular micro cloud adjustment system270 and FIG. 3 .

FIG. 5 illustrates a method 500 for dynamically updating an existingvehicular micro cloud 120. The method 500 will be described from theviewpoint of the connected vehicle 102 of FIG. 2 and the vehicular microcloud adjustment system 270 of FIG. 3 . However, the method 500 may beadapted to be executed in any one of several different situations andnot necessarily by the connected vehicle 102 of FIG. 2 and/or thevehicular micro cloud adjustment system 270 of FIG. 3 .

At step 510, the environment parameter determination module 320 cancause the processor(s) 210 to determine one or more parameters of anenvironment around a plurality of vehicles. As previously mentioned, theenvironment parameter determination module 320 can determine theparameters by receiving sensor data from vehicle sensors or by receivinginformation from external sources such as other vehicles or databaseservers.

At step 520, the impact identification module 330 can cause theprocessor(s) 210 to identify an impact of the one or more parameters ofthe environment on one or more of the plurality of vehicles associatedwith the existing vehicular micro cloud 120. As an example, the impactidentification module 330 can identify the impact based on a statisticalanalysis and/or machine learning methods. An example of an impact caninclude a portion of a road along the travel route of the vehicle(s)being inaccessible.

At step 530, the vehicular micro cloud update module 340 can cause theprocessor(s) 210 to identify one or more properties of the existingvehicular micro cloud 120, as discussed above.

At step 540, the vehicular micro cloud update module 340 can cause theprocessor(s) 210 to determine which adjustment to the properties of theexisting vehicular micro cloud 120 can address the impact. The vehicularmicro cloud update module 340 may use any suitable algorithm, aspreviously discussed, to determine which adjustment to the properties ofthe existing vehicular micro cloud 120 can address the impact.

At step 550, the vehicular micro cloud update module 340 can cause theprocessor(s) 210 to update the one or more properties based on thedetermination. The vehicular micro cloud update module 340 can transmitthe updated properties to the current cloud leader 104 or the vehicularmicro cloud update module 340 can select a new cloud leader and transmitthe updated properties to the newly selected cloud leader, as previouslydiscussed.

A first non-limiting example of the operation of the vehicular microcloud adjustment system 270 and/or one or more of the methods will nowbe described in relation to FIGS. 6A-6B. FIGS. 6A-6B show an example ofa dynamic vehicular micro cloud adjustment scenario 600.

In FIG. 6A, a stationary vehicular micro cloud 120 can exist at anintersection M. Connected vehicles 602 travelling through theintersection can join and/or exit the existing vehicular micro cloud120. The connected vehicle 604, which is similar to vehicle 102, can bea cloud leader 104 in the existing vehicular micro cloud 120, as theconnected vehicle 604 travels through the intersection. In this example,the existing vehicular micro cloud 120 can have the followingproperties: safety as the priority type, stationary as the mobilitytype, independent as the dependency type, pre-assigned as the origintype, hybrid as the communication type, traffic flow as the reason,improve awareness as the collaboration objective, and maximizeintersection safety as the optimization method. The vehicular microcloud adjustment system 270 can be located in the cloud leader 104, theserver 130, and/or any other connected vehicle 102.

The vehicular micro cloud adjustment system 270, or more specifically,the environment parameter determination module 320 can determine one ormore parameters of the environment around the intersection and thevehicles proximate to the intersection. As shown in FIG. 6A, twovehicles 602A, 602B have collided. The environment parameterdetermination module 320 can receive information about the environmentfrom, as an example, the cloud leader 604 or a server 130. The cloudleader 604 can observe the collision using vehicle sensors 221 and cantransmit the information to the environment parameter determinationmodule 320. The environment parameter determination module 320 cancommunicate with the server 130 and receive information from the server130 indicating that there is upcoming traffic. As an example, the server130 can obtain the information using sensors or by accessing a trafficcontrol database.

The vehicular micro cloud adjustment system 270, or more specifically,the impact identification module 330 can identify an impact of theparameters of the environment on the vehicle(s) associated with theexisting vehicular micro cloud 120. The impact identification module 330can determine that the impact of the collision can be traffic congestionbased on the information that includes a vehicle collision at theintersection, the number of vehicles in the intersection and the numberof vehicles approaching the intersection. The impact identificationmodule 330 can further determine that traffic congestion can increasethe risk of additional collisions. As previously mentioned, the impactidentification module 330 can use any suitable algorithm to determinethe impact of the collision on the vehicles in the environment.

The vehicular micro cloud adjustment system 270, or more specificallythe vehicular micro cloud update module 340 can identify one or moreproperties of the existing vehicular micro cloud 120. The vehicularmicro cloud update module 340 can identify the properties by requestingthe information from, as an example, the cloud leader 604 or the server130. Alternatively and/or in addition, the vehicular micro cloud updatemodule 340 can observe the environment to determine the properties ofthe vehicular micro cloud 120. In this example, the vehicular microcloud update module 340 can request the information from the cloudleader 604 and the cloud leader 604 can provide the properties of thevehicular micro cloud 120 as listed above.

The vehicular micro cloud adjustment system 270, or more specificallythe vehicular micro cloud update module 340 can determine whichadjustment to the one or more properties of the existing vehicular microcloud 120 can address the impact. In this case, the impact is trafficcongestion which can lead to safety risks such as a risk of additionalcollisions. The vehicular micro cloud update module 340 can determinethe properties that a vehicular micro cloud 120 can have to assistvehicles travelling through the environment. As an example, thevehicular micro cloud update module 340 can access a database thatmatches the impacts to the related properties of a vehicular micro cloud120. As another example and as previously mentioned, the vehicular microcloud update module 340 can apply any suitable algorithm to determinethe properties of the vehicular micro cloud 120. In this example, thevehicular micro cloud update module 340 can determine the followingproperties—safety as the priority type, stationary as the mobility type,interdependent as the dependency type, on-demand as the origin type,hybrid as the communication type, vehicle collision as the reason,mitigate traffic congestion as the collaboration objective, and minimizesafety risk as the optimization method.

The vehicular micro cloud adjustment system 270, or more specificallythe vehicular micro cloud update module 340 can compare the originalreason and the new reason. In this case, the vehicular micro cloudupdate module 340 can compare the original reason, which is traffic flowwith the new reason, which is a vehicle collision, and can determinethat the original reason and the new reason are different. In responseto determining that the original reason and the new reason aredifferent, the vehicular micro cloud update module 340 can update theproperties of the existing cloud by transmitting a message to the cloudleader 604 to adjust the properties of the vehicular micro cloud 120. Inthis case, in response to receiving the message, the cloud leader 604can adjust the dependency type from independent to interdependent. Inthis example and as shown in FIG. 6B, the server 130 can transmit amessage to the approaching vehicles, instructing the approachingvehicles to form vehicular micro clouds 620 that are interdependent.When the approaching vehicles form interdependent vehicular micro clouds620 and the existing vehicular micro cloud 120 adjusts from anindependent dependency type to an interdependent dependency type, theexisting vehicular micro cloud 120 and the newly formed vehicular microclouds 620, as well as the vehicle members 602 are able to collaborateand exchange information. As such the cloud leader 604 of the existingvehicular micro cloud 120 can send updates about the vehicle collisionand access at the intersection to the newly formed vehicular microclouds 620.

A second non-limiting example of the operation of the vehicular microcloud adjustment system 270 and/or one or more of the methods will nowbe described in relation to FIGS. 7A-7B. FIGS. 7A-7B show anotherexample of a dynamic vehicular micro cloud adjustment scenario 700.

In FIG. 7A, a mobile vehicular micro cloud 120 can exist around a masstransportation vehicle such as a commuter vehicle. Connected vehiclestravelling proximate to the existing vehicular micro cloud 120 and thecommuter vehicle 704 can join and/or exit the existing vehicular microcloud 120. The commuter vehicle 704 can share similarities with vehicle102. The commuter vehicle 704 can be a cloud leader 104 in the existingvehicular micro cloud 120, as the commuter vehicle 704 travels along aroad. The commuter vehicle 704 can be large and as such a driver of thecommuter vehicle 704 may have multiple blind spots. As such, thecommuter vehicle 704 can be a vehicular micro cloud member so as toshare information with other vehicular micro cloud members in order toremain safe and provide a smooth and comfortable ride for passengers inthe commuter vehicle 704. In this example, the existing vehicular microcloud 120 can have the following properties, comfort as the prioritytype, mobile as the mobility type, independent as the dependency type,on-demand as the origin type, ad-hoc as the communication type, trafficflow as the reason, promote travel comfort as the collaborationobjective, and maximize travel comfort as the optimization method.

The vehicular micro cloud adjustment system 270, or more specifically,the environment parameter determination module 320 can determine one ormore parameters of the environment around the commuter vehicle 704 andthe vehicles 702 proximate to the commuter vehicle 704. As shown in FIG.7B, the commuter vehicle 704 can stop to drop off and/or pick up one ormore passengers. The environment parameter determination module 320 canreceive information about the environment from, as an example, thecommuter vehicle 704. In such a case and as an example, the environmentparameter determination module 320 can receive information from thecommuter vehicle sensors, indicating that the commuter vehicle 704 hasstopped, and as such, can determine that the commuter vehicle 704 hasstopped.

The vehicular micro cloud adjustment system 270, or more specifically,the impact identification module 330 can identify an impact of theparameters of the environment on the vehicle(s) 702 associated with theexisting vehicular micro cloud 120. In other words, the impactidentification module 330 can identify the impact of the parameters ofthe environment on the vehicles 702 approaching the stopped commutervehicle 704. The impact identification module 330 can determine that theimpact can be traffic congestion based on the commuter vehicle 704 beingstopped and blocking traffic, and the number of vehicles 702 travellingon the road towards the commuter vehicle 704. The impact identificationmodule 330 can further determine that traffic congestion can increasethe risk of a collision. As previously mentioned, the impactidentification module 330 can use any suitable algorithm to determinethe impact of the stopped commuter vehicle 704 on the vehicles 702 inthe environment.

The vehicular micro cloud adjustment system 270, or more specificallythe vehicular micro cloud update module 340 can identify one or moreproperties of the existing vehicular micro cloud 120. The vehicularmicro cloud update module 340 can identify the properties by requestingthe information from, as an example, the cloud leader. The vehicularmicro cloud adjustment system 270, or more specifically the vehicularmicro cloud update module 340 can determine which adjustment to the oneor more properties of the existing vehicular micro cloud 120 can addressthe impact. In this case, the impact is traffic congestion which canlead to safety risks such as a risk of a collision between vehicles or acollision between a vehicle and a passenger boarding or deboarding thecommuter vehicle. As previously mentioned, the vehicular micro cloudupdate module 340 can determine the properties that a vehicular microcloud 120 can have to assist vehicles travelling through theenvironment. In this example, the vehicular micro cloud update module340 can determine the following properties—safety as the priority type,stationary as the mobility type, interdependent as the dependency type,on-demand as the origin type, ad-hoc as the communication type, stoppedcommuter vehicle as the reason, improve environment awareness as thecollaboration objective, and minimize safety risk as the optimizationmethod.

The vehicular micro cloud adjustment system 270, or more specificallythe vehicular micro cloud update module 340 can compare the originalreason and the new reason. In this case, the vehicular micro cloudupdate module 340 can compare the original reason, which is safety andcomfort for a mobile commuter vehicle with the new reason, which issafety around a stopped commuter vehicle 704, and can determine that theoriginal reason and the new reason are different. In response todetermining that the original reason and the new reason are different,the vehicular micro cloud update module 340 can update the properties ofthe existing cloud by transmitting a message to the cloud leader, whichis the commuter vehicle 704 in this case, to adjust the properties ofthe vehicular micro cloud 120. In response to receiving the message, thecommuter vehicle 704 can adjust the mobility type of the vehicular microcloud 120 from mobile to stationary. In this example, an approachingvehicle 702 near the commuter vehicle 704 can detect that there is astopped commuter vehicle 704 using vehicle sensors 221. The approachingvehicle 702 can instruct other approaching vehicles to form vehicularmicro clouds 720 that are interdependent. When the approaching vehiclesform interdependent vehicular micro clouds 720 and the existingvehicular micro cloud 120 adjusts from an independent dependency type toan interdependent dependency type, the existing vehicular micro cloud120 and the newly formed vehicular micro clouds 720, as well as thevehicle members 702 are able to collaborate and exchange information. Assuch the commuter vehicle 704 of the existing vehicular micro cloud 120can send updates about the location of the commuter vehicle 704 and howlong the commuter vehicle 704 intends to be stopped to the newly formedvehicular micro clouds 720.

It will be appreciated that arrangements described herein can providenumerous benefits, including one or more of the benefits mentionedherein. For example, arrangements described herein can result in sharingresources between vehicular micro cloud members to address eventsoccurring in the surrounding environment.

FIG. 2 will now be discussed in full detail as an example environmentwithin which the system and methods disclosed herein may operate. Insome instances, the connected vehicle 102 can be configured to switchselectively between an autonomous mode, one or more semi-autonomousoperational modes, and/or a manual mode. Such switching can beimplemented in a suitable manner, now known or later developed. “Manualmode” means that all of or a majority of the navigation and/ormaneuvering of the vehicle is performed according to inputs receivedfrom a user (e.g., human driver). In one or more arrangements, theconnected vehicle 102 can be a conventional vehicle that is configuredto operate in only a manual mode.

In one or more embodiments, the connected vehicle 102 can be anautonomous vehicle, a semi-autonomous vehicle, and/or a manual vehicle.As used herein, “autonomous vehicle” refers to a vehicle that operatesin an autonomous mode. “Autonomous mode” refers to navigating and/ormaneuvering the connected vehicle 102 along a travel route using one ormore computing systems to control the connected vehicle 102 with minimalor no input from a human driver. In one or more embodiments, theconnected vehicle 102 is highly automated or completely automated. Inone embodiment, the connected vehicle 102 is configured with one or moresemi-autonomous operational modes in which one or more computing systemsperform a portion of the navigation and/or maneuvering of the connectedvehicle 102 along a travel route, and a vehicle operator (i.e., driver)provides inputs to the connected vehicle 102 to perform a portion of thenavigation and/or maneuvering of the connected vehicle 102 along atravel route.

The connected vehicle 102 can include one or more processors 210. In oneor more arrangements, the processor(s) 210 can be a main processor ofthe connected vehicle 102. For instance, the processor(s) 210 can be anelectronic control unit (ECU). The connected vehicle 102 can include oneor more data stores 215 for storing one or more types of data. The datastore 215 can include volatile and/or non-volatile memory. Examples ofsuitable data stores 215 include RAM (Random Access Memory), flashmemory, ROM (Read Only Memory), PROM (Programmable Read-Only Memory),EPROM (Erasable Programmable Read-Only Memory), EEPROM (ElectricallyErasable Programmable Read-Only Memory), registers, magnetic disks,optical disks, hard drives, or any other suitable storage medium, or anycombination thereof. The data store 215 can be a component of theprocessor(s) 210, or the data store 215 can be operatively connected tothe processor(s) 210 for use thereby. The term “operatively connected,”as used throughout this description, can include direct or indirectconnections, including connections without direct physical contact.

In one or more arrangements, the one or more data stores 215 can includemap data 216. The map data 216 can include maps of one or moregeographic areas. In some instances, the map data 216 can includeinformation or data on roads, traffic control devices, road markings,structures, features, and/or landmarks in the one or more geographicareas. The map data 216 can be in any suitable form. In some instances,the map data 216 can include aerial views of an area. In some instances,the map data 216 can include ground views of an area, including360-degree ground views. The map data 216 can include measurements,dimensions, distances, and/or information for one or more items includedin the map data 216 and/or relative to other items included in the mapdata 216. The map data 216 can include a digital map with informationabout road geometry. The map data 216 can be high quality and/or highlydetailed.

In one or more arrangements, the one or more data stores 215 can includemap data 216. The map data 216 can include maps of one or moregeographic areas. In some instances, the map data 216 can includeinformation or data on roads, traffic control devices, road markings,structures, features, and/or landmarks in the one or more geographicareas. The map data 216 can be in any suitable form. In some instances,the map data 216 can include aerial views of an area. In some instances,the map data 216 can include ground views of an area, including360-degree ground views. The map data 216 can include measurements,dimensions, distances, and/or information for one or more items includedin the map data 216 and/or relative to other items included in the mapdata 216. The map data 216 can include a digital map with informationabout road geometry. The map data 216 can be high quality and/or highlydetailed.

In one or more arrangements, the map data 216 can include one or moreterrain maps 217. The terrain map(s) 217 can include information aboutthe ground, terrain, roads, surfaces, and/or other features of one ormore geographic areas. The terrain map(s) 217 can include elevation datain the one or more geographic areas. The map data 216 can be highquality and/or highly detailed. The terrain map(s) 217 can define one ormore ground surfaces, which can include paved roads, unpaved roads,land, and other things that define a ground surface.

In one or more arrangements, the map data 216 can include one or morestatic obstacle maps 218. The static obstacle map(s) 218 can includeinformation about one or more static obstacles located within one ormore geographic areas. A “static obstacle” is a physical object whoseposition does not change or substantially change over a period of timeand/or whose size does not change or substantially change over a periodof time. Examples of static obstacles include trees, buildings, curbs,fences, railings, medians, utility poles, statues, monuments, signs,benches, furniture, mailboxes, large rocks, hills. The static obstaclescan be objects that extend above ground level. The one or more staticobstacles included in the static obstacle map(s) 218 can have locationdata, size data, dimension data, material data, and/or other dataassociated with it. The static obstacle map(s) 218 can includemeasurements, dimensions, distances, and/or information for one or morestatic obstacles. The static obstacle map(s) 218 can be high qualityand/or highly detailed. The static obstacle map(s) 218 can be updated toreflect changes within a mapped area.

The one or more data stores 215 can include sensor data 219. In thiscontext, “sensor data” means any information about the sensors that theconnected vehicle 102 is equipped with, including the capabilities andother information about such sensors. As will be explained below, theconnected vehicle 102 can include the sensor system 220. The sensor data219 can relate to one or more sensors of the sensor system 220. As anexample, in one or more arrangements, the sensor data 219 can includeinformation on one or more LIDAR sensors 224 of the sensor system 220.

In some instances, at least a portion of the map data 216 and/or thesensor data 219 can be located in one or more data stores 215 locatedonboard the connected vehicle 102. Alternatively, or in addition, atleast a portion of the map data 216 and/or the sensor data 219 can belocated in one or more data stores 215 that are located remotely fromthe connected vehicle 102.

As noted above, the connected vehicle 102 can include the sensor system220. The sensor system 220 can include one or more sensors. “Sensor”means any device, component and/or system that can detect, and/or sensesomething. The one or more sensors can be configured to detect, and/orsense in real-time. As used herein, the term “real-time” means a levelof processing responsiveness that a user or system senses assufficiently immediate for a particular process or determination to bemade, or that enables the processor to keep up with some externalprocess.

In arrangements in which the sensor system 220 includes a plurality ofsensors, the sensors can work independently from each other.Alternatively, two or more of the sensors can work in combination witheach other. In such a case, the two or more sensors can form a sensornetwork. The sensor system 220 and/or the one or more sensors can beoperatively connected to the processor(s) 210, the data store(s) 215,and/or another element of the connected vehicle 102 (including any ofthe elements shown in FIG. 2 ). The sensor system 220 can acquire dataof at least a portion of the external environment of the connectedvehicle 102 (e.g., nearby vehicles).

The sensor system 220 can include any suitable type of sensor. Variousexamples of different types of sensors will be described herein.However, it will be understood that the embodiments are not limited tothe particular sensors described. The sensor system 220 can include oneor more vehicle sensors 221. The vehicle sensor(s) 221 can detect,determine, and/or sense information about the connected vehicle 102itself. In one or more arrangements, the vehicle sensor(s) 221 can beconfigured to detect, and/or sense position and orientation changes ofthe connected vehicle 102, such as, for example, based on inertialacceleration. In one or more arrangements, the vehicle sensor(s) 221 caninclude one or more accelerometers, one or more gyroscopes, an inertialmeasurement unit (IMU), a dead-reckoning system, a global navigationsatellite system (GNSS), a global positioning system (GPS), a navigationsystem 247, and/or other suitable sensors. The vehicle sensor(s) 221 canbe configured to detect, and/or sense one or more characteristics of theconnected vehicle 102. In one or more arrangements, the vehiclesensor(s) 221 can include a speedometer to determine a current speed ofthe connected vehicle 102.

Alternatively, or in addition, the sensor system 220 can include one ormore environment sensors 222 configured to acquire, and/or sense drivingenvironment data. “Driving environment data” includes data orinformation about the external environment in which the vehicle islocated or one or more portions thereof. For example, the one or moreenvironment sensors 222 can be configured to detect, quantify and/orsense obstacles in at least a portion of the external environment of theconnected vehicle 102 and/or information/data about such obstacles. Suchobstacles may be stationary objects and/or dynamic objects. The one ormore environment sensors 222 can be configured to detect, measure,quantify and/or sense other objects in the external environment of theconnected vehicle 102, such as, for example, lane markers, signs,traffic lights, traffic signs, lane lines, crosswalks, curbs proximatethe connected vehicle 102, off-road objects, electronic roadsidedevices, etc. The one or more environment sensors 222 can be configuredto determine whether the objects with electronic capability arefunctional by wirelessly transmitting messages to and receiving messagesfrom the objects.

Various examples of sensors of the sensor system 220 will be describedherein. The example sensors may be part of the one or more environmentsensors 222 and/or the one or more vehicle sensors 221. However, it willbe understood that the embodiments are not limited to the particularsensors described.

As an example, in one or more arrangements, the sensor system 220 caninclude one or more radar sensors 223, one or more LIDAR sensors 224,one or more sonar sensors 225, one or more cameras 226, and/or one ormore communication sensors 227. In one or more arrangements, the one ormore cameras 226 can be high dynamic range (HDR) cameras or infrared(IR) cameras. The communication sensor(s) 227 such as radio frequencyidentification (RFID) and near-field communication (NFC) readers maycommunicate with electronic objects such as RFID and/or NFC tags in theenvironment using any suitable means of communication such as Wi-Fi,Bluetooth, vehicle-to-infrastructure (V2I) wireless communication, V2Xwireless communication, RFIC, and NFC.

The connected vehicle 102 can include an input system 230. An “inputsystem” includes any device, component, system, element or arrangementor groups thereof that enable information/data to be entered into amachine. The input system 230 can receive an input from a vehiclepassenger (e.g., a driver or a passenger). The connected vehicle 102 caninclude an output system 235. An “output system” includes any device,component, or arrangement or groups thereof that enable information/datato be presented to a vehicle passenger (e.g., a person, a vehiclepassenger, etc.).

The connected vehicle 102 can include one or more transceivers 280. Asused herein, “transceiver” is defined as a component or a group ofcomponents that transmit signals, receive signals or transmit andreceive signals, whether wirelessly or through a hard-wired connection.The transceiver(s) 280 can enable communications between the connectedvehicle 102 and other elements of the DVMCA system 100 including otherconnected vehicles 102. The transceiver(s) 280 can be any suitabletransceivers used to access a network, access point, node or otherdevice for the transmission and receipt of data. The transceiver(s) 280may be wireless transceivers using any one of a number of wirelesstechnologies, now known or in the future.

The connected vehicle 102 can include one or more vehicle systems 240.Various examples of the one or more vehicle systems 240 are shown inFIG. 2 . However, the connected vehicle 102 can include more, fewer, ordifferent vehicle systems. It should be appreciated that althoughparticular vehicle systems are separately defined, each or any of thesystems or portions thereof may be otherwise combined or segregated viahardware and/or software within the connected vehicle 102. The connectedvehicle 102 can include a propulsion system 241, a braking system 242, asteering system 243, throttle system 244, a transmission system 245, asignaling system 246, and/or a navigation system 247. Each of thesesystems can include one or more devices, components, and/or acombination thereof, now known or later developed.

The navigation system 247 can include one or more devices, applications,and/or combinations thereof, now known or later developed, configured todetermine the geographic location of the connected vehicle 102 and/or todetermine a travel route for the connected vehicle 102. The navigationsystem 247 can include one or more mapping applications to determine atravel route for the connected vehicle 102. The navigation system 247can include a global positioning system, a local positioning system or ageolocation system.

The processor(s) 210, the vehicular micro cloud adjustment system 270,and/or the autonomous driving module(s) 260 can be operatively connectedto communicate with the various vehicle systems 240 and/or individualcomponents thereof. For example, returning to FIG. 2 , the processor(s)210 and/or the autonomous driving module(s) 260 can be in communicationto send and/or receive information from the various vehicle systems 240to control the movement, speed, maneuvering, heading, direction, etc. ofthe connected vehicle 102. The processor(s) 210, the vehicular microcloud adjustment system 270, and/or the autonomous driving module(s) 260may control some or all of these vehicle systems 240 and, thus, may bepartially or fully autonomous.

The processor(s) 210, the vehicular micro cloud adjustment system 270,and/or the autonomous driving module(s) 260 can be operatively connectedto communicate with the various vehicle systems 240 and/or individualcomponents thereof. For example, returning to FIG. 2 , the processor(s)210, the vehicular micro cloud adjustment system 270, and/or theautonomous driving module(s) 260 can be in communication to send and/orreceive information from the various vehicle systems 240 to control themovement, speed, maneuvering, heading, direction, etc. of the connectedvehicle 102. The processor(s) 210, the vehicular micro cloud adjustmentsystem 270, and/or the autonomous driving module(s) 260 may control someor all of these vehicle systems 240.

The processor(s) 210, the vehicular micro cloud adjustment system 270,and/or the autonomous driving module(s) 260 may be operable to controlthe navigation and/or maneuvering of the connected vehicle 102 bycontrolling one or more of the vehicle systems 240 and/or componentsthereof. For instance, when operating in an autonomous mode, theprocessor(s) 210, the vehicular micro cloud adjustment system 270,and/or the autonomous driving module(s) 260 can control the directionand/or speed of the connected vehicle 102. The processor(s) 210, thevehicular micro cloud adjustment system 270, and/or the autonomousdriving module(s) 260 can cause the connected vehicle 102 to accelerate(e.g., by increasing the supply of fuel provided to the engine),decelerate (e.g., by decreasing the supply of fuel to the engine and/orby applying brakes) and/or change direction (e.g., by turning the fronttwo wheels). As used herein, “cause” or “causing” means to make, force,compel, direct, command, instruct, and/or enable an event or action tooccur or at least be in a state where such event or action may occur,either in a direct or indirect manner.

The connected vehicle 102 can include one or more actuators 250. Theactuators 250 can be any element or combination of elements operable tomodify, adjust and/or alter one or more of the vehicle systems 240 orcomponents thereof to responsive to receiving signals or other inputsfrom the processor(s) 210 and/or the autonomous driving module(s) 260.Any suitable actuator can be used. For instance, the one or moreactuators 250 can include motors, pneumatic actuators, hydraulicpistons, relays, solenoids, and/or piezoelectric actuators, just to namea few possibilities.

The connected vehicle 102 can include one or more modules, at least someof which are described herein. The modules can be implemented ascomputer-readable program code that, when executed by a processor 210,implement one or more of the various processes described herein. One ormore of the modules can be a component of the processor(s) 210, or oneor more of the modules can be executed on and/or distributed among otherprocessing systems to which the processor(s) 210 is operativelyconnected. The modules can include instructions (e.g., program logic)executable by one or more processor(s) 210. Alternatively, or inaddition, one or more data store 215 may contain such instructions.

In one or more arrangements, one or more of the modules described hereincan include artificial or computational intelligence elements, e.g.,neural network, fuzzy logic or other machine learning algorithms.Further, in one or more arrangements, one or more of the modules can bedistributed among a plurality of the modules described herein. In one ormore arrangements, two or more of the modules described herein can becombined into a single module.

The connected vehicle 102 can include one or more autonomous drivingmodules 260. The autonomous driving module(s) 260 can be configured toreceive data from the sensor system 220 and/or any other type of systemcapable of capturing information relating to the connected vehicle 102and/or the external environment of the connected vehicle 102. In one ormore arrangements, the autonomous driving module(s) 260 can use suchdata to generate one or more driving scene models. The autonomousdriving module(s) 260 can determine position and velocity of theconnected vehicle 102. The autonomous driving module(s) 260 candetermine the location of obstacles, obstacles, or other environmentalfeatures including traffic signs, trees, shrubs, neighboring vehicles,pedestrians, etc.

The autonomous driving module(s) 260 can be configured to receive,and/or determine location information for obstacles within the externalenvironment of the connected vehicle 102 for use by the processor(s)210, and/or one or more of the modules described herein to estimateposition and orientation of the connected vehicle 102, vehicle positionin global coordinates based on signals from a plurality of satellites,or any other data and/or signals that could be used to determine thecurrent state of the connected vehicle 102 or determine the position ofthe connected vehicle 102 with respect to its environment for use ineither creating a map or determining the position of the connectedvehicle 102 in respect to map data.

The autonomous driving module(s) 260 either independently or incombination with the vehicular micro cloud adjustment system 270 can beconfigured to determine travel path(s), current autonomous drivingmaneuvers for the connected vehicle 102, future autonomous drivingmaneuvers and/or modifications to current autonomous driving maneuversbased on data acquired by the sensor system 220, driving scene models,and/or data from any other suitable source such as determinations fromthe sensor data 219. “Driving maneuver” means one or more actions thataffect the movement of a vehicle. Examples of driving maneuvers include:accelerating, decelerating, braking, turning, moving in a lateraldirection of the connected vehicle 102, changing travel lanes, merginginto a travel lane, and/or reversing, just to name a few possibilities.The autonomous driving module(s) 260 can be configured to implementdetermined driving maneuvers. The autonomous driving module(s) 260 cancause, directly or indirectly, such autonomous driving maneuvers to beimplemented. As used herein, “cause” or “causing” means to make,command, instruct, and/or enable an event or action to occur or at leastbe in a state where such event or action may occur, either in a director indirect manner. The autonomous driving module(s) 260 can beconfigured to execute various vehicle functions and/or to transmit datato, receive data from, interact with, and/or control the connectedvehicle 102 or one or more systems thereof (e.g., one or more of vehiclesystems 240).

Detailed embodiments are disclosed herein. However, it is to beunderstood that the disclosed embodiments are intended only as examples.Therefore, specific structural and functional details disclosed hereinare not to be interpreted as limiting, but merely as a basis for theclaims and as a representative basis for teaching one skilled in the artto variously employ the aspects herein in virtually any appropriatelydetailed structure. Further, the terms and phrases used herein are notintended to be limiting but rather to provide an understandabledescription of possible implementations. Various embodiments are shownin FIGS. 1-8 but the embodiments are not limited to the illustratedstructure or application.

The flowcharts and block diagrams in the figures illustrate thearchitecture, functionality, and operation of possible implementationsof systems, methods, and computer program products according to variousembodiments. In this regard, each block in the flowcharts or blockdiagrams may represent a module, segment, or portion of code, whichcomprises one or more executable instructions for implementing thespecified logical function(s). It should also be noted that, in somealternative implementations, the functions noted in the block may occurout of the order noted in the figures. For example, two blocks shown insuccession may, in fact, be executed substantially concurrently, or theblocks may sometimes be executed in the reverse order, depending uponthe functionality involved.

The systems, components and/or processes described above can be realizedin hardware or a combination of hardware and software and can berealized in a centralized fashion in one processing system or in adistributed fashion where different elements are spread across severalinterconnected processing systems. Any kind of processing system oranother apparatus adapted for carrying out the methods described hereinis suited. A typical combination of hardware and software can be aprocessing system with computer-usable program code that, when beingloaded and executed, controls the processing system such that it carriesout the methods described herein. The systems, components and/orprocesses also can be embedded in a computer-readable storage, such as acomputer program product or other data programs storage device, readableby a machine, tangibly embodying a program of instructions executable bythe machine to perform methods and processes described herein. Theseelements also can be embedded in an application product which comprisesall the features enabling the implementation of the methods describedherein and, which when loaded in a processing system, is able to carryout these methods.

Furthermore, arrangements described herein may take the form of acomputer program product embodied in one or more computer-readable mediahaving computer-readable program code embodied, e.g., stored, thereon.Any combination of one or more computer-readable media may be utilized.The computer-readable medium may be a computer-readable signal medium ora computer-readable storage medium. The phrase “computer-readablestorage medium” means a non-transitory storage medium. Acomputer-readable storage medium may be, for example, but not limitedto, an electronic, magnetic, optical, electromagnetic, infrared, orsemiconductor system, apparatus, or device, or any suitable combinationof the foregoing. More specific examples (a non-exhaustive list) of thecomputer-readable storage medium would include the following: a portablecomputer diskette, a hard disk drive (HDD), a solid-state drive (SSD), aread-only memory (ROM), an erasable programmable read-only memory (EPROMor Flash memory), a portable compact disc read-only memory (CD-ROM), adigital versatile disc (DVD), an optical storage device, a magneticstorage device, or any suitable combination of the foregoing. In thecontext of this document, a computer-readable storage medium may be anytangible medium that can contain, or store a program for use by or inconnection with an instruction execution system, apparatus, or device.

Generally, modules, as used herein, include routines, programs, objects,components, data structures, and so on that perform particular tasks orimplement particular data types. In further aspects, a memory generallystores the noted modules. The memory associated with a module may be abuffer or cache embedded within a processor, a RAM, a ROM, a flashmemory, or another suitable electronic storage medium. In still furtheraspects, a module as envisioned by the present disclosure is implementedas an application-specific integrated circuit (ASIC), a hardwarecomponent of a system on a chip (SoC), as a programmable logic array(PLA), or as another suitable hardware component that is embedded with adefined configuration set (e.g., instructions) for performing thedisclosed functions.

Program code embodied on a computer-readable medium may be transmittedusing any appropriate medium, including but not limited to wireless,wireline, optical fiber, cable, RF, etc., or any suitable combination ofthe foregoing. Computer program code for carrying out operations foraspects of the present arrangements may be written in any combination ofone or more programming languages, including an object-orientedprogramming language such as Java™, Smalltalk, C++ or the like andconventional procedural programming languages, such as the “C”programming language or similar programming languages. The program codemay execute entirely on the user's computer, partly on the user'scomputer, as a stand-alone software package, partly on the user'scomputer and partly on a remote computer, or entirely on the remotecomputer or server. In the latter scenario, the remote computer may beconnected to the user's computer through any type of network, includinga local area network (LAN) or a wide area network (WAN), or theconnection may be made to an external computer (for example, through theInternet using an Internet Service Provider).

The terms “a” and “an,” as used herein, are defined as one or more thanone. The term “plurality,” as used herein, is defined as two or morethan two. The term “another,” as used herein, is defined as at least asecond or more. The terms “including” and/or “having,” as used herein,are defined as comprising (i.e., open language). The phrase “at leastone of . . . and . . . ” as used herein refers to and encompasses anyand all possible combinations of one or more of the associated listeditems. As an example, the phrase “at least one of A, B, and C” includesA only, B only, C only, or any combination thereof (e.g., AB, AC, BC orABC).

Aspects herein can be embodied in other forms without departing from thespirit or essential attributes thereof. Accordingly, reference should bemade to the following claims, rather than to the foregoingspecification, as indicating the scope hereof.

What is claimed is:
 1. A method for dynamically updating an existing vehicular micro cloud, the method comprising: determining one or more parameters of an environment around a plurality of vehicles; identifying an impact of the one or more parameters of the environment on one or more of the plurality of vehicles associated with the existing vehicular micro cloud; identifying an original reason for the existing vehicular micro cloud; determining whether one or more properties associated with the original reason for the existing vehicular micro cloud can address the impact; and updating the one or more properties based on the determination, the one or more properties including at least one of a priority, a mobility type, a dependency type, a communication category, or a collaboration criteria.
 2. The method of claim 1, wherein the determining the one or more parameters of the environment around the plurality of the vehicles includes monitoring the environment.
 3. The method of claim 1, wherein the one or more properties include a priority, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the priority to safety, comfort, or time management can address the impact.
 4. The method of claim 1, wherein the one or more properties include a mobility type, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the mobility type to mobile or to stationary can address the impact.
 5. The method of claim 1, wherein the one or more properties include a dependency type, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the dependency type to independent or to interdependent can address the impact.
 6. The method of claim 1, wherein the one or more properties include a communication category, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the communication category to an ad-hoc communication or a hybrid communication can address the impact.
 7. The method of claim 1, wherein the one or more properties include a collaboration criteria, wherein the collaboration criteria includes at least one of an objective function and an optimization method, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the objective function or the optimization method can address the impact.
 8. The method of claim 1, wherein the existing vehicular micro cloud communicates with one or more other vehicular micro clouds, forming a vehicular macro cloud.
 9. A method for dynamically updating an existing vehicular micro cloud, the method comprising: determining one or more parameters of an environment around a plurality of vehicles; identifying an impact of the one or more parameters of the environment on one or more of the plurality of vehicles associated with the existing vehicular micro cloud; identifying one or more properties of the existing vehicular micro cloud; determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact, wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes: identifying an original reason for the existing vehicular micro cloud; identifying a new reason for the existing vehicular micro cloud based on the one or more parameters; determining that the original reason and the new reason are different; and in response to determining that the original reason and the new reason are different, determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact based on the new reason; and updating the one or more properties based on the determination.
 10. The method of claim 9, wherein the original reason is based on one of traffic flow, traffic density, a vehicle accident, a road closure, an unusual event, and a risk, and wherein the new reason is based on one of traffic flow, traffic density, a vehicle accident, a road closure, an unusual event, and a risk.
 11. A system for dynamically updating an existing vehicular micro cloud, the system comprising: one or more processors; and a memory in communication with the one or more processors, the memory including: an environment parameter determination module including instructions that when executed by the one or more processors cause the one or more processors to determine one or more parameters of an environment around a plurality of vehicles; an impact identification module including instructions that when executed by the one or more processors cause the one or more processors to identify an impact of the one or more parameters of the environment on one or more of the plurality of vehicles associated with the existing vehicular micro cloud; and a vehicular micro cloud update module including instructions that when executed by the one or more processors cause the one or more processors to: identify an original reason for the existing vehicular micro cloud; determine whether one or more properties associated with the original reason for the existing vehicular micro cloud can address the impact; and update the one or more properties based on the determination.
 12. The system of claim 11, wherein the environment parameter determination module further includes instructions that when executed by the one or more processors cause the one or more processors to monitor the environment.
 13. The system of claim 11, wherein the one or more properties include a priority, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the priority to safety, comfort, or time management can address the impact.
 14. The system of claim 11, wherein the one or more properties include a mobility type, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the mobility type to mobile or to stationary can address the impact.
 15. The system of claim 11, wherein the one or more properties include a dependency type, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the dependency type to independent or to interdependent can address the impact.
 16. The system of claim 11, wherein the one or more properties include a communication category, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the communication category to an ad-hoc communication or a hybrid communication can address the impact.
 17. The system of claim 11, wherein the one or more properties include a collaboration criteria, wherein the collaboration criteria includes at least one of an objective function and an optimization method, and wherein the determining which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact further includes at least one of determining whether an adjustment of the objective function or the optimization method can address the impact.
 18. The system of claim 11, wherein the existing vehicular micro cloud communicates with one or more other vehicular micro clouds, forming a vehicular macro cloud.
 19. A system for dynamically updating an existing vehicular micro cloud, the system comprising: one or more processors; and a memory in communication with the one or more processors, the memory including: an environment parameter determination module including instructions that when executed by the one or more processors cause the one or more processors to determine one or more parameters of an environment around a plurality of vehicles; an impact identification module including instructions that when executed by the one or more processors cause the one or more processors to identify an impact of the one or more parameters of the environment on one or more of the plurality of vehicles associated with the existing vehicular micro cloud; and a vehicular micro cloud update module including instructions that when executed by the one or more processors cause the one or more processors to: identify one or more properties of the existing vehicular micro cloud; determine which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact; wherein the vehicular micro cloud update module further includes instructions that when executed by the one or more processors cause the one or more processors to: identify an original reason for the existing vehicular micro cloud; identify a new reason for the existing vehicular micro cloud based on the one or more parameters of the environment; determine that the original reason and the new reason are different; and in response to determining that the original reason and the new reason are different, determine which adjustment to the one or more properties of the existing vehicular micro cloud can address the impact based on the new reason; and update the one or more properties based on the determination.
 20. The system of claim 19, wherein the original reason is based on one of traffic flow, traffic density, a vehicle accident, a road closure, an unusual event, and a risk, and wherein the new reason is based on one of traffic flow, traffic density, a vehicle accident, a road closure, an unusual event, and a risk. 